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Título : Mathematical Models for Registration and Applications to Medical Imaging Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Scherzer, Otmar Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2006 Colección: Mathematics in Industry, ISSN 1612-3956 num. 10 Número de páginas: X, 191 p. 54 illus., 12 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-540-34767-5 Idioma : Inglés (eng) Palabras clave: Mathematics Radiology Computer graphics Mathematical models Modeling and Industrial Imaging, Vision, Pattern Recognition Graphics Imaging / Clasificación: 51 Matemáticas Resumen: Image registration is an emerging topic in image processing with many applications in medical imaging, picture and movie processing. The classical problem of image registration is concerned with ?nding an appropriate transformation between two data sets. This fuzzy de?nition of registration requires a mathematical modeling and in particular a mathematical speci?cation of the terms appropriate transformations and correlation between data sets. Depending on the type of application, typically Euler, rigid, plastic, elastic deformations are considered. The variety of similarity p measures ranges from a simpleL distance between the pixel values of the data to mutual information or entropy distances. This goal of this book is to highlight by some experts in industry and medicine relevant and emerging image registration applications and to show new emerging mathematical technologies in these areas. Currently, many registration application are solved based on variational prin- ple requiring sophisticated analysis, such as calculus of variations and the theory of partial differential equations, to name but a few. Due to the numerical compl- ity of registration problems ef?cient numerical realization are required. Concepts like multi-level solver for partial differential equations, non-convex optimization, and so on play an important role. Mathematical and numerical issues in the area of registration are discussed by some of the experts in this volume. Moreover, the importance of registration for industry and medical imaging is discussed from a medical doctor and from a manufacturer point of view Nota de contenido: Numerical Methods -- A Generalized Image Registration Framework using Incomplete Image Information – with Applications to Lesion Mapping -- Medical Image Registration and Interpolation by Optical Flow with Maximal Rigidity -- Registration of Histological Serial Sectionings -- Computational Methods for Nonlinear Image Registration -- A Survey on Variational Optic Flow Methods for Small Displacements -- Applications -- Fast Image Matching for Generation of Panorama Ultrasound -- Inpainting of Movies Using Optical Flow -- Medical Applications -- Multimodality Registration in Daily Clinical Practice -- Colour Images En línea: http://dx.doi.org/10.1007/978-3-540-34767-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34984 Mathematical Models for Registration and Applications to Medical Imaging [documento electrónico] / SpringerLink (Online service) ; Scherzer, Otmar . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2006 . - X, 191 p. 54 illus., 12 illus. in color : online resource. - (Mathematics in Industry, ISSN 1612-3956; 10) .
ISBN : 978-3-540-34767-5
Idioma : Inglés (eng)
Palabras clave: Mathematics Radiology Computer graphics Mathematical models Modeling and Industrial Imaging, Vision, Pattern Recognition Graphics Imaging / Clasificación: 51 Matemáticas Resumen: Image registration is an emerging topic in image processing with many applications in medical imaging, picture and movie processing. The classical problem of image registration is concerned with ?nding an appropriate transformation between two data sets. This fuzzy de?nition of registration requires a mathematical modeling and in particular a mathematical speci?cation of the terms appropriate transformations and correlation between data sets. Depending on the type of application, typically Euler, rigid, plastic, elastic deformations are considered. The variety of similarity p measures ranges from a simpleL distance between the pixel values of the data to mutual information or entropy distances. This goal of this book is to highlight by some experts in industry and medicine relevant and emerging image registration applications and to show new emerging mathematical technologies in these areas. Currently, many registration application are solved based on variational prin- ple requiring sophisticated analysis, such as calculus of variations and the theory of partial differential equations, to name but a few. Due to the numerical compl- ity of registration problems ef?cient numerical realization are required. Concepts like multi-level solver for partial differential equations, non-convex optimization, and so on play an important role. Mathematical and numerical issues in the area of registration are discussed by some of the experts in this volume. Moreover, the importance of registration for industry and medical imaging is discussed from a medical doctor and from a manufacturer point of view Nota de contenido: Numerical Methods -- A Generalized Image Registration Framework using Incomplete Image Information – with Applications to Lesion Mapping -- Medical Image Registration and Interpolation by Optical Flow with Maximal Rigidity -- Registration of Histological Serial Sectionings -- Computational Methods for Nonlinear Image Registration -- A Survey on Variational Optic Flow Methods for Small Displacements -- Applications -- Fast Image Matching for Generation of Panorama Ultrasound -- Inpainting of Movies Using Optical Flow -- Medical Applications -- Multimodality Registration in Daily Clinical Practice -- Colour Images En línea: http://dx.doi.org/10.1007/978-3-540-34767-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34984 Ejemplares
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Título : The Mathematics of Medical Imaging : A Beginner’s Guide Tipo de documento: documento electrónico Autores: Timothy G. Feeman ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Colección: Springer Undergraduate Texts in Mathematics and Technology, ISSN 1867-5506 Número de páginas: XII, 141 p Il.: online resource ISBN/ISSN/DL: 978-0-387-92712-1 Idioma : Inglés (eng) Palabras clave: Mathematics Radiology Computer science graphics Functional analysis Integral transforms Operational calculus Biomedical engineering Analysis Imaging / Transforms, Calculus Math Applications in Science Imaging, Vision, Pattern Recognition and Graphics Engineering Clasificación: 51 Matemáticas Resumen: A Beginner's Guide to the Mathematics of Medical Imaging presents the basic mathematics of computerized tomography – the CT scan – for an audience of undergraduates in mathematics and engineering. Assuming no prior background in advanced mathematical analysis, topics such as the Fourier transform, sampling, and discrete approximation algorithms are introduced from scratch and are developed within the context of medical imaging. A chapter on magnetic resonance imaging focuses on manipulation of the Bloch equation, the system of differential equations that is the foundation of this important technology. The text is self-contained with a range of practical exercises, topics for further study, and an ample bibliography, making it ideal for use in an undergraduate course in applied or engineering mathematics, or by practitioners in radiology who want to know more about the mathematical foundations of their field Nota de contenido: X-rays -- The Radon Transform -- Back Projection -- Complex Numbers -- The Fourier Transform -- Two Big Theorems -- Filters and Convolution -- Discrete Image Reconstruction -- Algebraic Reconstruction Techniques -- MRI#x2014;An Overview En línea: http://dx.doi.org/10.1007/978-0-387-92712-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33526 The Mathematics of Medical Imaging : A Beginner’s Guide [documento electrónico] / Timothy G. Feeman ; SpringerLink (Online service) . - New York, NY : Springer New York, 2010 . - XII, 141 p : online resource. - (Springer Undergraduate Texts in Mathematics and Technology, ISSN 1867-5506) .
ISBN : 978-0-387-92712-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Radiology Computer science graphics Functional analysis Integral transforms Operational calculus Biomedical engineering Analysis Imaging / Transforms, Calculus Math Applications in Science Imaging, Vision, Pattern Recognition and Graphics Engineering Clasificación: 51 Matemáticas Resumen: A Beginner's Guide to the Mathematics of Medical Imaging presents the basic mathematics of computerized tomography – the CT scan – for an audience of undergraduates in mathematics and engineering. Assuming no prior background in advanced mathematical analysis, topics such as the Fourier transform, sampling, and discrete approximation algorithms are introduced from scratch and are developed within the context of medical imaging. A chapter on magnetic resonance imaging focuses on manipulation of the Bloch equation, the system of differential equations that is the foundation of this important technology. The text is self-contained with a range of practical exercises, topics for further study, and an ample bibliography, making it ideal for use in an undergraduate course in applied or engineering mathematics, or by practitioners in radiology who want to know more about the mathematical foundations of their field Nota de contenido: X-rays -- The Radon Transform -- Back Projection -- Complex Numbers -- The Fourier Transform -- Two Big Theorems -- Filters and Convolution -- Discrete Image Reconstruction -- Algebraic Reconstruction Techniques -- MRI#x2014;An Overview En línea: http://dx.doi.org/10.1007/978-0-387-92712-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33526 Ejemplares
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Título : Ricci Flow for Shape Analysis and Surface Registration : Theories, Algorithms and Applications Tipo de documento: documento electrónico Autores: Wei Zeng ; SpringerLink (Online service) ; Xianfeng David Gu Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: SpringerBriefs in Mathematics, ISSN 2191-8198 Número de páginas: XI, 139 p. 69 illus., 49 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-8781-4 Idioma : Inglés (eng) Palabras clave: Mathematics Computer graphics mathematics Geometry Convex geometry Discrete Imaging, Vision, Pattern Recognition and Graphics Computational Numerical Analysis Clasificación: 51 Matemáticas Resumen: Ricci Flow for Shape Analysis and Surface Registration introduces the beautiful and profound Ricci flow theory in a discrete setting. By using basic tools in linear algebra and multivariate calculus, readers can deduce all the major theorems in surface Ricci flow by themselves. The authors adapt the Ricci flow theory to practical computational algorithms, apply Ricci flow for shape analysis and surface registration, and demonstrate the power of Ricci flow in many applications in medical imaging, computer graphics, computer vision and wireless sensor network. Due to minimal pre-requisites, this book is accessible to engineers and medical experts, including educators, researchers, students and industry engineers who have an interest in solving real problems related to shape analysis and surface registration. Nota de contenido: 1. Introduction -- 2. Computational -- 3. Computational Geometry -- 4. Differential Geometry of Surface -- 5. Riemann Surface -- 6. Ricci Flow -- 7. Topological Algorithms -- 8. Harmonic Maps -- 9. Discrete Ricci Flow -- 10. Shape Analysis -- 11. Surface Diffeomorphism -- 12. Medical Imaging Applications -- 13. Computer Vision Applications -- 14. Computer Graphics Applications -- 15. Network Applications. En línea: http://dx.doi.org/10.1007/978-1-4614-8781-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32402 Ricci Flow for Shape Analysis and Surface Registration : Theories, Algorithms and Applications [documento electrónico] / Wei Zeng ; SpringerLink (Online service) ; Xianfeng David Gu . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XI, 139 p. 69 illus., 49 illus. in color : online resource. - (SpringerBriefs in Mathematics, ISSN 2191-8198) .
ISBN : 978-1-4614-8781-4
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer graphics mathematics Geometry Convex geometry Discrete Imaging, Vision, Pattern Recognition and Graphics Computational Numerical Analysis Clasificación: 51 Matemáticas Resumen: Ricci Flow for Shape Analysis and Surface Registration introduces the beautiful and profound Ricci flow theory in a discrete setting. By using basic tools in linear algebra and multivariate calculus, readers can deduce all the major theorems in surface Ricci flow by themselves. The authors adapt the Ricci flow theory to practical computational algorithms, apply Ricci flow for shape analysis and surface registration, and demonstrate the power of Ricci flow in many applications in medical imaging, computer graphics, computer vision and wireless sensor network. Due to minimal pre-requisites, this book is accessible to engineers and medical experts, including educators, researchers, students and industry engineers who have an interest in solving real problems related to shape analysis and surface registration. Nota de contenido: 1. Introduction -- 2. Computational -- 3. Computational Geometry -- 4. Differential Geometry of Surface -- 5. Riemann Surface -- 6. Ricci Flow -- 7. Topological Algorithms -- 8. Harmonic Maps -- 9. Discrete Ricci Flow -- 10. Shape Analysis -- 11. Surface Diffeomorphism -- 12. Medical Imaging Applications -- 13. Computer Vision Applications -- 14. Computer Graphics Applications -- 15. Network Applications. En línea: http://dx.doi.org/10.1007/978-1-4614-8781-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32402 Ejemplares
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Título : Visualization and Processing of Tensor Fields Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Joachim Weickert ; Hans Hagen Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2006 Colección: Mathematics and Visualization, ISSN 1612-3786 Número de páginas: XV, 481 p Il.: online resource ISBN/ISSN/DL: 978-3-540-31272-7 Idioma : Inglés (eng) Palabras clave: Mathematics Radiology Computer graphics Image processing Mathematical analysis Analysis (Mathematics) Visualization Differential geometry Imaging / Imaging, Vision, Pattern Recognition and Graphics Processing Vision Geometry Clasificación: 51 Matemáticas Resumen: Matrix-valued data sets - so-called second order tensor fields - have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state-of-the-art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students Nota de contenido: An Introduction to Tensors -- Feature Detection with Tensors -- Adaptive Structure Tensors and their Applications -- On the Concept of a Local Greyvalue Distribution and the Adaptive Estimation of a Structure Tensor -- Low-level Feature Detection Using the Boundary Tensor -- Diffusion Tensor Imaging -- An Introduction to Computational Diffusion MRI: the Diffusion Tensor and Beyond -- Random Noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections -- An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications -- Anatomy-Based Visualizations of Diffusion Tensor Images of Brain White Matter -- Variational Regularization of Multiple Diffusion Tensor Fields -- Higher Rank Tensors in Diffusion MRI -- Visualization of Tensor Fields -- Strategies for Direct Visualization of Second-Rank Tensor Fields -- Tensor Invariants and their Gradients -- Visualizing the Topology of Symmetric, Second-Order, Time-Varying Two-Dimensional Tensor Fields -- Degenerate 3D Tensors -- Locating Closed Hyperstreamlines in Second Order Tensor Fields -- Tensor Field Visualization Using a Metric Interpretation -- Tensor Field Transformations -- Symmetric Positive-Definite Matrices: From Geometry to Applications and Visualization -- Continuous Tensor Field Approximation of Diffusion Tensor MRI data -- Tensor Field Interpolation with PDEs -- Diffusion-Tensor Image Registration -- Image Processing Methods for Tensor Fields -- Tensor Median Filtering and M-Smoothing -- Mathematical Morphology on Tensor Data Using the Loewner Ordering -- A Local Structure Measure for Anisotropic Regularization of Tensor Fields -- Tensor Field Regularization using Normalized Convolution and Markov Random Fields in a Bayesian Framework -- PDEs for Tensor Image Processing En línea: http://dx.doi.org/10.1007/3-540-31272-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34936 Visualization and Processing of Tensor Fields [documento electrónico] / SpringerLink (Online service) ; Joachim Weickert ; Hans Hagen . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2006 . - XV, 481 p : online resource. - (Mathematics and Visualization, ISSN 1612-3786) .
ISBN : 978-3-540-31272-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Radiology Computer graphics Image processing Mathematical analysis Analysis (Mathematics) Visualization Differential geometry Imaging / Imaging, Vision, Pattern Recognition and Graphics Processing Vision Geometry Clasificación: 51 Matemáticas Resumen: Matrix-valued data sets - so-called second order tensor fields - have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state-of-the-art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students Nota de contenido: An Introduction to Tensors -- Feature Detection with Tensors -- Adaptive Structure Tensors and their Applications -- On the Concept of a Local Greyvalue Distribution and the Adaptive Estimation of a Structure Tensor -- Low-level Feature Detection Using the Boundary Tensor -- Diffusion Tensor Imaging -- An Introduction to Computational Diffusion MRI: the Diffusion Tensor and Beyond -- Random Noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections -- An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications -- Anatomy-Based Visualizations of Diffusion Tensor Images of Brain White Matter -- Variational Regularization of Multiple Diffusion Tensor Fields -- Higher Rank Tensors in Diffusion MRI -- Visualization of Tensor Fields -- Strategies for Direct Visualization of Second-Rank Tensor Fields -- Tensor Invariants and their Gradients -- Visualizing the Topology of Symmetric, Second-Order, Time-Varying Two-Dimensional Tensor Fields -- Degenerate 3D Tensors -- Locating Closed Hyperstreamlines in Second Order Tensor Fields -- Tensor Field Visualization Using a Metric Interpretation -- Tensor Field Transformations -- Symmetric Positive-Definite Matrices: From Geometry to Applications and Visualization -- Continuous Tensor Field Approximation of Diffusion Tensor MRI data -- Tensor Field Interpolation with PDEs -- Diffusion-Tensor Image Registration -- Image Processing Methods for Tensor Fields -- Tensor Median Filtering and M-Smoothing -- Mathematical Morphology on Tensor Data Using the Loewner Ordering -- A Local Structure Measure for Anisotropic Regularization of Tensor Fields -- Tensor Field Regularization using Normalized Convolution and Markov Random Fields in a Bayesian Framework -- PDEs for Tensor Image Processing En línea: http://dx.doi.org/10.1007/3-540-31272-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34936 Ejemplares
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Título : Visualization and Processing of Tensor Fields : Advances and Perspectives Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; David H. Laidlaw ; Joachim Weickert Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2009 Colección: Mathematics and Visualization, ISSN 1612-3786 Número de páginas: XVII, 376 p Il.: online resource ISBN/ISSN/DL: 978-3-540-88378-4 Idioma : Inglés (eng) Palabras clave: Mathematics Computer science graphics Image processing mathematics Computational and Numerical Analysis of Computing Imaging, Vision, Pattern Recognition Graphics Processing Vision Clasificación: 51 Matemáticas Nota de contenido: Models for Diffusion MRI -- Modelling, Fitting and Sampling in Diffusion MRI -- Tensors, Polynomials and Models for Directional Data -- A Mixture of Wisharts (MOW) Model for Multifiber Reconstruction -- The Algebra of Fourth-Order Tensors with Application to Diffusion MRI -- Higher-Level Analysis of Diffusion Images -- Structure-Specific Statistical Mapping of White Matter Tracts -- Analysis of Distance/Similarity Measures for Diffusion Tensor Imaging -- Tensor Field Visualization -- Tensor Glyph Warping: Visualizing Metric Tensor Fields using Riemannian Exponential Maps -- Interactive Volume Rendering of Diffusion Tensor Data -- Dense Glyph Sampling for Visualization -- Tensor Field Analysis in the Physical Sciences -- The Role of Tensor Fields for Satellite Gravity Gradiometry -- Tensor Visualization and Defect Detection for Nematic Liquid Crystals using Shape Characteristics -- A Tensor Approach to Elastography Analysis and Visualization -- Tensor Image Structure Models -- A Higher-Order Structure Tensor -- Monogenic Curvature Tensor as Image Model -- Filtering with Tensors -- A General Structure Tensor Concept and Coherence-Enhancing Diffusion Filtering for Matrix Fields -- Coordinates-Based Diffusion Over the Space of Symmetric Positive-Definite Matrices -- Variational Methods for Denoising Matrix Fields -- An Operator Algebraic Inverse Scale Space Method for Symmetric Matrix Valued Images En línea: http://dx.doi.org/10.1007/978-3-540-88378-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34043 Visualization and Processing of Tensor Fields : Advances and Perspectives [documento electrónico] / SpringerLink (Online service) ; David H. Laidlaw ; Joachim Weickert . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2009 . - XVII, 376 p : online resource. - (Mathematics and Visualization, ISSN 1612-3786) .
ISBN : 978-3-540-88378-4
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer science graphics Image processing mathematics Computational and Numerical Analysis of Computing Imaging, Vision, Pattern Recognition Graphics Processing Vision Clasificación: 51 Matemáticas Nota de contenido: Models for Diffusion MRI -- Modelling, Fitting and Sampling in Diffusion MRI -- Tensors, Polynomials and Models for Directional Data -- A Mixture of Wisharts (MOW) Model for Multifiber Reconstruction -- The Algebra of Fourth-Order Tensors with Application to Diffusion MRI -- Higher-Level Analysis of Diffusion Images -- Structure-Specific Statistical Mapping of White Matter Tracts -- Analysis of Distance/Similarity Measures for Diffusion Tensor Imaging -- Tensor Field Visualization -- Tensor Glyph Warping: Visualizing Metric Tensor Fields using Riemannian Exponential Maps -- Interactive Volume Rendering of Diffusion Tensor Data -- Dense Glyph Sampling for Visualization -- Tensor Field Analysis in the Physical Sciences -- The Role of Tensor Fields for Satellite Gravity Gradiometry -- Tensor Visualization and Defect Detection for Nematic Liquid Crystals using Shape Characteristics -- A Tensor Approach to Elastography Analysis and Visualization -- Tensor Image Structure Models -- A Higher-Order Structure Tensor -- Monogenic Curvature Tensor as Image Model -- Filtering with Tensors -- A General Structure Tensor Concept and Coherence-Enhancing Diffusion Filtering for Matrix Fields -- Coordinates-Based Diffusion Over the Space of Symmetric Positive-Definite Matrices -- Variational Methods for Denoising Matrix Fields -- An Operator Algebraic Inverse Scale Space Method for Symmetric Matrix Valued Images En línea: http://dx.doi.org/10.1007/978-3-540-88378-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34043 Ejemplares
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